{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TorchDyn Quickstart\n",
    "\n",
    "**TorchDyn is the toolkit for continuous models in PyTorch. Play with state-of-the-art architectures or use its powerful libraries to create your own.**\n",
    "\n",
    "\n",
    "Central to the `torchdyn` approach are continuous neural networks, where *width*, *depth* (or both) are taken to their infinite limit. On the optimization front, we consider continuous \"data-stream\" regimes and gradient flow methods, where the dataset represents a time-evolving signal processed by the neural network to adapt its parameters. \n",
    "\n",
    "By providing a centralized, easy-to-access collection of model templates, tutorial and application notebooks, we hope to speed-up research in this area and ultimately contribute to turning neural differential equations into an effective tool for control, system identification and common machine learning tasks.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys ; sys.path.append('../')\n",
    "from torchdyn.models import *\n",
    "from torchdyn.datasets import *\n",
    "from torchdyn import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate data from a static toy dataset \n",
    "\n",
    "We’ll be generating data from toy datasets. In torchdyn, we provide a wide range of datasets often use to benchmark and understand Neural ODEs. Here we will use the classic moons dataset and train a Neural ODE for binary classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "d = ToyDataset()\n",
    "X, yn = d.generate(n_samples=512, noise=1e-1, dataset_type='moons')        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 216x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "colors = ['orange', 'blue'] \n",
    "fig = plt.figure(figsize=(3,3))\n",
    "ax = fig.add_subplot(111)\n",
    "for i in range(len(X)):\n",
    "    ax.scatter(X[i,0], X[i,1], s=1, color=colors[yn[i].int()])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Generated data can be easily loaded in the dataloader with standard `PyTorch` calls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.utils.data as data\n",
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "\n",
    "X_train = torch.Tensor(X).to(device)\n",
    "y_train = torch.LongTensor(yn.long()).to(device)\n",
    "train = data.TensorDataset(X_train, y_train)\n",
    "trainloader = data.DataLoader(train, batch_size=len(X), shuffle=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We utilize [Pytorch Lightning](https://github.com/PyTorchLightning/pytorch-lightning) to handle training loops, logging and general bookkeeping. This allows `torchdyn` and Neural Differential Equations to have access to modern best practices for training and experiment reproducibility. \n",
    "\n",
    "In particular, we combine modular `torchdyn` models with `LightningModules` via a `Learner` class:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch.nn as nn\n",
    "import pytorch_lightning as pl\n",
    "\n",
    "class Learner(pl.LightningModule):\n",
    "    def __init__(self, model:nn.Module):\n",
    "        super().__init__()\n",
    "        self.model = model\n",
    "    \n",
    "    def forward(self, x):\n",
    "        return self.model(x)\n",
    "    \n",
    "    def training_step(self, batch, batch_idx):\n",
    "        x, y = batch      \n",
    "        y_hat = self.model(x)   \n",
    "        loss = nn.CrossEntropyLoss()(y_hat, y)\n",
    "        logs = {'train_loss': loss}\n",
    "        return {'loss': loss, 'log': logs}   \n",
    "    \n",
    "    def configure_optimizers(self):\n",
    "        return torch.optim.Adam(self.model.parameters(), lr=0.01)\n",
    "\n",
    "    def train_dataloader(self):\n",
    "        return trainloader"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define a  Neural ODE"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Analogously to most forward neural models we want to realize a map \n",
    "\n",
    "$$\n",
    "        x \\mapsto \\hat y\n",
    "$$\n",
    "\n",
    "where  $\\hat y$ becomes the best approximation of a true output $y$ given an input $x$.\n",
    "In torchdyn you can define very simple Neural ODE models of the form \n",
    "\n",
    "$$ \\left\\{\n",
    "    \\begin{aligned}\n",
    "        \\dot{z}(s) &= f(z(s), \\theta)\\\\\n",
    "        z(0) &= x\\\\\n",
    "        \\hat y & = z(1)\n",
    "    \\end{aligned}\n",
    "    \\right. \\quad s\\in[0,1]\n",
    "$$\n",
    "\n",
    "by just specifying a neural network $f$ and giving some simple settings.\n",
    "\n",
    "**Note:** This Neural ODE model is of *depth-invariant* type as neither $f$ explicitly depend on $s$ nor the parameters $\\theta$ are depth-varying. Together with their *depth-variant* counterpart with $s$ concatenated in the vector field was first proposed and implemented by [[Chen T. Q. et al, 2018]](https://arxiv.org/abs/1806.07366)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define the vector field (DEFunc) \n",
    "\n",
    "The first step is to define any PyTorch `torch.nn.Module`. This takes the role of the Neural ODE vector field $f(h,\\theta)$ "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "f = nn.Sequential(\n",
    "        nn.Linear(2, 16),\n",
    "        nn.Tanh(),\n",
    "        nn.Linear(16, 2)                       \n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this case we chose $f$ to be a simple MLP with one hidden layer and $\\tanh$ activation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define the NeuralDE"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The final step to define a Neural ODE is to instantiate the torchdyn's class `NeuralDE` passing some customization arguments and `f` itself.\n",
    "\n",
    "In this case we specify:\n",
    "* we compute backward gradients with the `'adjoint'` method.\n",
    "* we will use the `'dopri5'` (Dormand-Prince) ODE solver from `torchdiffeq`;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = NeuralDE(f, sensitivity='adjoint', solver='dopri5').to(device)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GPU available: True, used: False\n",
      "TPU available: False, using: 0 TPU cores\n",
      "\n",
      "  | Name  | Type     | Params\n",
      "-----------------------------------\n",
      "0 | model | NeuralDE | 82    \n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "162c083266064150b94ea3fd5fb48897",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', description='Training', layout=Layout(flex='2'), max…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "learn = Learner(model)\n",
    "trainer = pl.Trainer(min_epochs=200, max_epochs=300)\n",
    "trainer.fit(learn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With the method `trajectory` of `NeuralDE` objects you can quickly evaluate the entire trajectory of each data point in `X_train` on an interval `s_span`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "s_span = torch.linspace(0,1,100)\n",
    "trajectory = model.trajectory(X_train, s_span).detach().cpu()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot the Training Results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can first plot the trajectories of the data points in the depth domain $s$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Dimension 1')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x144 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "color=['orange', 'blue']\n",
    "\n",
    "fig = plt.figure(figsize=(10,2))\n",
    "ax0 = fig.add_subplot(121)\n",
    "ax1 = fig.add_subplot(122)\n",
    "for i in range(500):\n",
    "    ax0.plot(s_span, trajectory[:,i,0], color=color[int(yn[i])], alpha=.1);\n",
    "    ax1.plot(s_span, trajectory[:,i,1], color=color[int(yn[i])], alpha=.1);\n",
    "ax0.set_xlabel(r\"$s$ [Depth]\") ; ax0.set_ylabel(r\"$h_0(s)$\")\n",
    "ax1.set_xlabel(r\"$s$ [Depth]\") ; ax1.set_ylabel(r\"$z_1(s)$\")\n",
    "ax0.set_title(\"Dimension 0\") ; ax1.set_title(\"Dimension 1\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then the trajectory in the *state-space*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, the Neural ODE steers the data-points into regions of null loss with a continuous flow in the depth domain. Finally, we can also plot the learned vector field $f$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x1f3458fbe08>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# evaluate vector field\n",
    "n_pts = 50\n",
    "x = torch.linspace(trajectory[:,:,0].min(), trajectory[:,:,0].max(), n_pts)\n",
    "y = torch.linspace(trajectory[:,:,1].min(), trajectory[:,:,1].max(), n_pts)\n",
    "X, Y = torch.meshgrid(x, y) ; z = torch.cat([X.reshape(-1,1), Y.reshape(-1,1)], 1)\n",
    "f = model.defunc(0,z.to(device)).cpu().detach()\n",
    "fx, fy = f[:,0], f[:,1] ; fx, fy = fx.reshape(n_pts , n_pts), fy.reshape(n_pts, n_pts)\n",
    "# plot vector field and its intensity\n",
    "fig = plt.figure(figsize=(4, 4)) ; ax = fig.add_subplot(111)\n",
    "ax.streamplot(X.numpy().T, Y.numpy().T, fx.numpy().T, fy.numpy().T, color='black')\n",
    "ax.contourf(X.T, Y.T, torch.sqrt(fx.T**2+fy.T**2), cmap='RdYlBu')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Sweet! You trained your first Neural ODE! Now go on and learn more advanced models with the next tutorials**"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
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  "latex_envs": {
   "LaTeX_envs_menu_present": true,
   "autoclose": false,
   "autocomplete": true,
   "bibliofile": "biblio.bib",
   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 1,
   "hotkeys": {
    "equation": "Ctrl-E",
    "itemize": "Ctrl-I"
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   "labels_anchors": false,
   "latex_user_defs": false,
   "report_style_numbering": false,
   "user_envs_cfg": false
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  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
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    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
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    "_Feature"
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   "window_display": false
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 "nbformat": 4,
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}
